So yesterday I put together a blog post analysing how performance varies for batsmen based on which point in the match they come to the crease.
Today I’m going to show which players have performed the best in the Big Bash League and the Women’s Big Bash League, when their score is adjusted to reflect their opportunities.
This metric is based on this graph: how many runs does each batsman score, broken down by the over in which they entered the innings:
And here’s the same chart for women’s Twenty20 cricket:
The WBBL data includes the last four seasons of the state-based competition which preceded the WBBL, and it does appear that players in domestic Australian women’s Twenty20 cricket entering in the middle of the innings have performed better over the last five years. Continue reading “Top batsmen in the W/BBL adjusted for point in the game”
There’s a lot to be done to improve metrics for players in Twenty20 cricket. This summer I’ve mostly focused on team-level metrics that give you a sense of the whole game, not about the performance of individual players.
There’s a lot of focus in Twenty20 cricket on a player’s strike rate, and that is undoubtedly important. But it’s also important that a batsman is able to last a reasonable amount of time. Players who hit a six and then get out off their second ball on a regular basis will have an extremely high strike rate, but won’t be of much value to their team. So the ability to stay also has value.
When you consider this point, the old-fashioned batting average (the number of runs scored over the number of times your wicket has been taken) has value. Ideally we’d come up with another metric which can mix together these two simple measures to give a sense of the ability of a batsman to score fast but also stick around long enough to make an impact.
In this post, I’m going to focus on a particular datapoint which I think has value when making assessments of players: when they come into the match.
Not all balls are the same, and not all overs are the same. Generally matches follow a pattern where the number of runs scored speeds up as you head towards the end of the match (barring the loss of significant numbers of wickets). You can see that in this graph:
The powerplay covers the first six overs in Twenty20 matches. During this time teams may only place two fielders outside of the circle which marks out 30 yards from the pitch. Following the powerplay, teams may have up to five fielders outside the circle. This clearly has an impact on the game. While the first over is the lowest-scoring over of the match, runs are scored quite quickly in overs 3-6, before collapsing in over 7. It takes until around over 15 before the batting team usually surpasses the scoring rate of the powerplay, but the average number of runs scored per over exceeds nine runs for the final overs.
Obviously you would expect different performances from batsmen depending on when they enter the match. If a batsman enters earlier in the match, they are not expected to score as quickly, but they have more time to play, while those coming in later are expected to score at a faster rate but may not have time to score as many runs.
Continue reading “Better batting metrics – judging by point of entry”